News: OhioHealth Taps Qventus to Automate Care Operations Across the Enterprise Read now
The AMC needed to address systemic inefficiencies in patient flow to reduce an higher-than-desired average length of stay (LOS) and create more inpatient bed capacity.
Additionally, while the AMC believed it was capturing care gaps like malnutrition fairly effectively, their reliance on retrospective workflows created a critical blind spot. Without real-time identification and orchestration of intervention during the patient encounter, significant opportunities to reduce LOS, optimize clinical care, and secure appropriate coding reimbursement were quietly being missed.
The AMC implemented the Qventus Inpatient Capacity Solution and Malnutrition Care Automation, a Care Gap and Coding Automation Suite solution, to embed AI teammates directly into Oracle Health. This dual-pronged strategy automates highly effective discharge planning and prioritizes real-time orchestration to proactively close care gaps – starting first with Malnutrition.
Discharge Planning Assistant: Machine learning models—locally trained on your patients and care patterns—auto-populate aggressive, yet achievable EDD and dispositions directly into the EHR on the first morning after admission.
Flow Priority Assistant: Using sophisticated Machine Learning models that analyze patient and census data, our solution automatically sequences ancillary orders to best support patient flow and discharge success.
Care Gap Assistant: Identifies and orchestrates the closure of potential gaps in each care plan, including tracking patient-specific milestones.
Case Manager Assistant: Reviews care team notes to summarize relevant context from last 24 hours and helps support planned dispositions to prevent PAC denials.
Capacity Intelligence Assistant: Our solution accelerates patient flow by identifying in real-time the key actions needed to achieve discharge success.
Condition Detection Assistant: Ingests structured and unstructured data in real-time to identify at-risk patients
Care Gap Assistant: Pre-populates an order for a nutrition consult and prompts the provider within their workflow to sign off. It also surfaces intelligence into the dietitian’s worklist for better context as they prepare for evaluations.
Coding and Documentation Assistant: Ensures appropriate capture of clinical complexity in documentation to support accurate MCC/CC capture, improving reimbursement and quality metrics.
Impact Assistant: Qventus analytics provide visibility into provider response rate, condition capture lift, revenue gains, and detailed evidence to support audits and reduce denials.
Simplifying surgical scheduling: Qventus’ digital booking interface, TimeFinder, enables schedulers to easily find open time slots. The software determines the best-fit slots for any given case—factoring in things like day of week, time, the type of room and any special equipment needed, duration of procedure, and more—and offers a list of available slots that most closely fit the criteria. The clinic scheduler can book the time and submit the case request information with just a few clicks.
Improving block time utilization: Machine learning algorithms learn from a surgeon’s historical practice patterns and use that data to predict, up to a month in advance, time within each surgeon’s block that is unlikely to be used. When the system identifies a slot with a significantly high probability of going unused, it sends an automated “nudge” to the surgeon’s scheduler, requesting a release of the slot. To incentivize the release, the nudge includes a calculation of how much the release will improve the surgeon’s block utilization rate.
Proactively filling unused slots: Under a manual process, unused slots are often filled with the first available procedure, rather than the most appropriate one. The Qventus Perioperative Solution’s Available Time Outreach functionality analyzes the characteristics of available slots, matches them with surgeons’ predicted needs, then offers the best-fit slots via email to the surgeon who’s most likely to use it and who also represents the highest value to Banner Health. The scheduler can accept or decline with a few clicks. If they decline, the system automatically moves to the next most likely candidate.
Ut blandit pulvinar volutpat. Cras egestas sem turpis, non accumsan justo cursus viverra. Proin ipsum arcu, dignissim a enim eu, tristique eleifend orci. Etiam commodo dignissim nisi, sed finibus metus auctor in. Nulla venenatis porttitor risus non pretium. In rhoncus tempor mauris. Orci varius natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus.
Ut blandit pulvinar volutpat. Cras egestas sem turpis, non accumsan justo cursus viverra. Proin ipsum arcu, dignissim a enim eu, tristique eleifend orci. Etiam commodo dignissim nisi, sed finibus metus auctor in. Nulla venenatis porttitor risus non pretium. In rhoncus tempor mauris. Orci varius natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus.
Ut blandit pulvinar volutpat. Cras egestas sem turpis, non accumsan justo cursus viverra. Proin ipsum arcu, dignissim a enim eu, tristique eleifend orci. Etiam commodo dignissim nisi, sed finibus metus auctor in. Nulla venenatis porttitor risus non pretium. In rhoncus tempor mauris. Orci varius natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus.
